◆ Google Looker

Manage Looker PDTs

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskRefresh the 'customer_segmentation' PDT and the 'product_performance' PDT. Make sure they…+
Refresh the 'customer_segmentation' PDT and the 'product_performance' PDT. Make sure they complete before the Friday morning executive review.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptBefore the sales team sees these dashboards, make sure the PDTs are optimized. Identify any…+
Before the sales team sees these dashboards, make sure the PDTs are optimized. Identify any that are taking longer than an hour to build and suggest ways to speed them up so the dashboards load quickly for everyone.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentThe 'daily_sales_summary' PDT failed for the third time this week, and the sales ops team needs…+
The 'daily_sales_summary' PDT just failed to build again, and the sales ops team is asking for updated reports.
The 'daily_sales_summary' PDT failed for the third time this week, and the sales ops team needs their dashboards updated by EOD. I'm worried it's a data type mismatch from the new source, but I can't pinpoint it. What's the most likely cause for a persistent PDT build failure, and what's the fastest way to get it back online without breaking downstream reports?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI'm constantly reacting to PDT failures and slow builds, which eats into my time for strategic…+
I keep getting pulled into urgent PDT refresh issues that impact critical dashboards.
I'm constantly reacting to PDT failures and slow builds, which eats into my time for strategic analysis. This firefighting means I'm not proactively improving our data models. What habit should I change to prevent these recurring PDT issues and free up my time for more impactful work?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from Google Looker's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.